The impact on the inclusion of marine subsurface variables on habitat modelling of swordfish in the Indian Ocean

Species distribution models (SDM) have emerged as an important technique for defining and forecasting species habitats. In the maritime domain, species distribution models have historically been constructed primarily as two-dimensional species occurrence and environmental data, with a lack of understanding of the real ecological environments of species. Our capacity to examine subsurface marine characteristics has grown thanks to developments in models and technology, but their integration into SDM is still somewhat restricted. We explored the impact of adding subsurface environmental factors in SDM on species habitat suitability to define habitat variation of adult swordfish (Xiphias gladius) in the Indian Ocean using environmental data from various depth layers in the research region. Data from the 2017–2019 Chinese Indian Ocean tuna longline fishery observer were used to generate the species data. In order to determine the best depth for simulating swordfish habitat, we utilized MaxEnt to investigate the impacts of subsurface factors and combine several indicators to evaluate the model's effectiveness. The significance of environmental elements was quickly assessed, and the connection between habitat appropriateness and CPUE was skimmed over. The outcomes demonstrated that the model's effectiveness was increased by include subsurface environmental factors, displaying a clear increasing trend and stabilizing after reaching the ideal level (300 m). Although the adult swordfish's distribution range for habitat suitability shrank little as depth increased, its core habitat suitability value increased dramatically. Among all environmental factors, T and DO were closely related to adult swordfish habitat distribution. In contrast, there was no significant correlation between habitat suitability and CPUE. Incorporating three-dimensional environmental considerations into the model yields more realistic results than model results that consider habitat as two-dimensional. Develop explicit three-dimensional methods to better represent the distribution of marine species.